Sarah Seaton

2016 AFPGR Participant

 

 When will my baby go home? Investigating neonatal care for preterm babies

About Sarah

Sarah Seaton is a part-time PhD student in the Department of Health Sciences. Her PhD investigates statistical methods to predict length of stay in hospital for babies born preterm. She is funded by a prestigious NIHR Doctoral Research Fellowship which she was awarded in 2013. Sarah is supervised by Dr. Bradley Manktelow, Prof. Keith Abrams and Prof. Elizabeth Draper.

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About My Research

After they are born, many babies require specialist neonatal care, particularly if they have been born prematurely. Preterm babies have complex needs, and their risk of mortality can be very high. Often the two key questions which a parent has are: “will my baby survive?” and “when will my baby go home?” Both of these questions are complex to answer, although much research has investigated the survival of preterm babies.

Babies are likely to need different lengths of stay in the neonatal unit, with some requiring only a few hours, and others needing to stay for weeks or months. The care required by babies will be varied, some needing complex interventions such as respiratory support and others needing less invasive care such as phototherapy. Preterm babies, if they survive, are likely to need very long stays in the neonatal unit before they are discharged home. During this time they are likely to need many different types of care. However, irrespective of whether a baby survives or not, their time in hospital should be included in research, particularly for when considering the commissioning of services.

Previous research which has investigated how to predict length of stay has two issues: (1) babies who die are often excluded or included without appropriate adjustment; (2) estimates of length of stay do not consider the levels of care that a baby needs whilst in hospital. Without consideration of these issues, it is impossible to have a full and accurate picture of the needs of these babies.

Conventional statistical approaches are unable to resolve these two issues, and therefore a more sophisticated approach is needed. In this PhD an approach known as multistate modelling is used. This allows different ‘competing’ outcomes to be considered (i.e. death or discharge from the neonatal unit) where the occurrence of one prevents the other from occurring. The analysis can also consider intermediate events that occur before death or discharge, and these are considered to be the different levels of care, defined as: intensive care; high dependency care and special care.

All 162 neonatal units in England provided permission for use of data related to their preterm babies (24-31 weeks gestational age) in hospital between 2011 and 2014. Each year around 300,000 days of care are given to these babies, around half of which is intensive care and high dependency care. It is possible to estimate the probability of receiving different levels of care, or of having died or been discharged in the days following birth. These can be used to aide clinicians in the counselling of parents about length of stay, and for commissioners to consider for the allocation of resources. My poster will present preliminary results from this analysis.

Presenter_Sarah Seaton
Sarah standing with her poster at the 2016 Festival of Postgraduate Research

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